5G network slicing function migration mechanism based on particle swarm optimization algorithm by Qiang CHEN, Caixia LIU, Lingshu LI

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Optimal Pre-disaster and Post-disaster Scheduling of Mobile Energy Storage Considering the Influence of Transportation Network by XIE Peikun, LI Liang, SHI Yuanjie, SHENG Qing, LI Zhenkun

“…Furthermore， this strategy fully accounts for traffic flow changes in the transportation network， optimizes the selection of MES scheduling paths， reduces the negative impact of traffic congestion， and further improves the scheduling efficiency of the MES. …”
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Improved Virtual Potential Field Algorithm Based on Probability Model in Three-Dimensional Directional Sensor Networks by Junjie Huang, Lijuan Sun, Ruchuan Wang, Haiping Huang

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Improving the Efficiency of Screen Type Potato Sorting Machines by a Modification of the Sieve Drive Movement Algorithm by A. G. Ivanov, M. N. Erokhin, S. P. Kazantsev, P. V. Dorodov, I. I. Khuzyakhmetov, I. T. Khakimov

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Improving MPCitH with Preprocessing: Mask Is All You Need by Guowei Liu, Guoxiao Liu, Kaijie Jiang, Qingyuan Yu, Keting Jia, Puwen Wei, Meiqin Wang

“…Furthermore, we explore the independence of the mask, demonstrating that it can be calculated in parallel, which also enables the optimization of the masked witness calculation. Our optimized implementation of Picnic3 shows significant improvements. …”
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Application of an Improved Minimum Noise Amplitude Deconvolution for Bearing Fault Diagnosis by Ying Ma, Siming He, Entie Qi, Yu Wei

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Development of View Optimization Techniques for Structural Monitoring Systems Using Post-Processing of Structural Analysis and Image Processing by Yonghui Park

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An Intelligent 5G Unmanned Aerial Vehicle Path Optimization Algorithm for Offshore Wind Farm Inspection by Congxiao Jiang, Lingang Yang, Yuqing Gao, Jie Zhao, Wenne Hou, Fangmin Xu

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Comparative Performance of Autoencoders and Traditional Machine Learning Algorithms in Clinical Data Analysis for Predicting Post-Staged GKRS Tumor Dynamics by Simona Ruxandra Volovăț, Tudor Ovidiu Popa, Dragoș Rusu, Lăcrămioara Ochiuz, Decebal Vasincu, Maricel Agop, Călin Gheorghe Buzea, Cristian Constantin Volovăț

“…<b>Objectives:</b> The primary objective of this study is to assess whether integrating autoencoder-derived features into traditional ML models can improve their performance in predicting tumor dynamics three months post-GKRS in patients with brain metastases. …”
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A Novel Black Widow Optimization Algorithm Based on Lagrange Interpolation Operator for ResNet18 by Peiyang Wei, Can Hu, Jingyi Hu, Zhibin Li, Wen Qin, Jianhong Gan, Tinghui Chen, Hongping Shu, Mingsheng Shang

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Machine learning-based coalbed methane well production prediction and fracturing parameter optimization by HU Qiujia, LIU Chunchun, ZHANG Jianguo, CUI Xinrui, WANG Qian, WANG Qi, LI Jun, HE Shan

“…The model employs a random forest algorithm integrated with a multi-task learning strategy and utilizes a particle swarm optimization (PSO) algorithm to optimize fracturing parameters. …”
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Optimizing airway network efficiency with the A-star algorithm: a case study of Ho Chi Minh FIR by Ngoc Hoang Quan Nguyen, Thi Hoai An Vu, Hoang Mai Le, Mai Phuong Nguyen, Thi Thu Tra Le, Thi Thuy Trang Nguyen, Ngoc Nhu Y Nguyen

“…To address these challenges, this study proposes optimizing the airway network in 2D space using the A-star algorithm, tailored for the HCM FIR. …”
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TBESO-BP: an improved regression model for predicting subclinical mastitis by Kexin Han, Yongqiang Dai, Huan Liu, Junjie Hu, Leilei Liu, Zhihui Wang, Liping Wei

“…In comparison to six alternative models, the TBESO-BP model demonstrates superior accuracy and lower error values.DiscussionThe TBESO-BP model emerges as a precise tool for predicting subclinical mastitis in dairy cows. The TBESO algorithm notably enhances the efficacy of the BP neural network in regression prediction, ensuring elevated computational efficiency and practicality post-improvement.…”
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Diagnosing schizophrenia with routine blood tests: a comparative analysis of machine learning algorithms by Yavuz Selim Ogur, Ayse Erdogan Kaya, Nur Banu Ogur, Beyza Erdogan Akturk

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Improved empirical wavelet transform combined with particle swarm optimization-support vector machine for EEG-based depression recognition by Yongxin Wang, Longqi Xu, Hongxu Qian, Haijun Lin, Xuhui Zhang

“…Therefore, there is a pressing need to develop techniques for detecting early signs of depression to enable timely intervention and potentially improve recovery rates. In this paper, we propose an improved method for the early objective diagnosis of depression utilizing an empirical wavelet transform (EWT) technique enhanced by a particle swarm optimization-support vector machine (PSO-SVM) algorithm. …”
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ATHOS: A Hybrid Accelerator for PQC CRYSTALS-Algorithms Exploiting New CV-X-IF Interface by Alessandra Dolmeta, Maurizio Martina, Guido Masera

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AI-Driven Predictive Maintenance for Workforce and Service Optimization in the Automotive Sector by Şenda Yıldırım, Ahmet Deniz Yücekaya, Mustafa Hekimoğlu, Meltem Ucal, Mehmet Nafiz Aydin, İrem Kalafat

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Anti-Collision Path Planning and Tracking of Autonomous Vehicle Based on Optimized Artificial Potential Field and Discrete LQR Algorithm by Chaoxia Zhang, Zhihao Chen, Xingjiao Li, Ting Zhao

“…Comparative analysis of visual trajectories pre-optimization and post-optimization highlights improvements. …”
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A Robust Salp Swarm Algorithm for Photovoltaic Maximum Power Point Tracking Under Partial Shading Conditions by Boyan Huang, Kai Song, Shulin Jiang, Zhenqing Zhao, Zhiqiang Zhang, Cong Li, Jiawen Sun

“…Finally, the integration with P&O facilitates a meticulous search with a small step size, ensuring swift convergence and further mitigating post-convergence power oscillations. Both the simulations and the experimental results indicate that the proposed algorithm outperforms particle swarm optimization (PSO) and grey wolf optimization (GWO) in terms of convergence velocity, tracking precision, and the reduction in iteration power oscillation magnitude.…”
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Frequency regulation of two-area thermal and photovoltaic power system via flood algorithm by Serdar Ekinci, Davut Izci, Cebrail Turkeri, Aseel Smerat, Absalom E. Ezugwu, Laith Abualigah

“…The implementation details of the FLA-tuned PI controller are provided, and its performance is rigorously compared with PI controllers tuned using several state-of-the-art optimization techniques. These include sea horse optimization, salp swarm algorithm, whale optimization algorithm, shuffled frog-leaping algorithm, and firefly algorithm. …”
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